Machine Learning Research Engineer, Audio R&D
The AMT Audio team is looking for a highly motivated and dedicated research and development machine learning engineer to develop models for speech and audio applications.
The Audio and Media Technologies (AMT) is at the center of Apple’s innovative products, including the Mac, iPhone, iPad, Apple Watch, Apple TV, macOS, iOS, watchOS and tvOS. AMT’s Core Audio team provides audio foundation for various high profile features like Siri, phone calls, FaceTime, media capture, playback, and API’s for third party developers to enrich our platforms. The team is looking for hardworking engineers who are passionate about building audio software products for millions of customers and care about overall user experience. You will be revolutionizing and contributing to future audio technologies.
As part of the audio team, you will:
Develop machine learning model architectures for solving various problems in audio, including sound event detection, scene classification and context understanding.
Train, fine tune and compress models for production
Contribute to the team’s workflows building pipelines, writing datasets, and creating evaluation frameworks
Participate in cross-functional teams developing features and shipping products
Create intellectual property in the form of patents and publications
- Practical and theoretical knowledge of machine learning architecture design and training/testing methodologies.
- Experience building machine learning pipelines
- Excellent software architecture and programming skills in Python, C, C++
- Knowledge of audio technologies
- MS, in CS or EE, industry and research experience
- Proven experience in machine learning development, including audio and speech applications.
- Experience optimizing and compressing machine learning models for resource constrained platforms.
- Familiarity and experience with multimodal large language models (LLMs)
- Demonstrated innovation in machine learning (patents, publications)
- Fundamentals of audio and speech signal processing
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